Survey on Dynamic Query Forms for Database Queries

The databases used in today’s scientific research and web handle huge volumes of data. Such databases contain hundreds or even thousands of complex relations and attributes. The proposed system that implements dynamic query forms for non-relational data. The DQF captures a user’s preference and ranks query form components which assists the user in making decisions. Query form generation is an iterative process and initially requires user guidance in the form of feedback .The system automatically generates ranking list of form components, at each iteration and the desired form components are added by the user in Query forms. The ranking of form components depend on the captured user preference. The query results can be viewed at each iteration by the user after filling and submitting the query form. In order to measure the quality of the results generated by the Query form, a probabilistic model has been developed

Ranking based Dynamic Query forms for Database Queries

As the Environment of Internet continues to grow the users of searching the data also increases. By this development of web information and scientific databases it is not able to get user require results with the static query forms. The Dynamic Query forms are able to dynamically generate query forms with the selection of user interested components and rank the query form components. The creation of query forms is an iteration process and user selects interested components in iteration process. The form components ranking are based on the user interest and Fmeasure is used to measure the query form goodness. The incremental hierarchical data clustering framework is used to capture the user2019;s interest based on click feedback to input some keyword queries

Dynamic Query Forms for Database Queries Based on Ranking Mechanism.

A database is only a collection of large amount of data. We can persist, update, and delete the data to or from the database. To perform such a manipulation, we require a query interface. A user can communicate with the database. Problem here is traditional databases can’t give output as user’s satisfaction. To recover such a problem, we used Dynamic question type system: DQF, a question interface that is capable of dynamically generating question forms for users, different from document retrieval system. In information retrieval area, the users always perform several rounds of actions (refinement of question conditions) until they will get satisfaction. Some normal users can’t understand such programming languages. Even SQL, Oracle, etc databases are well-structured query languages, it can be challenging. Goal of this Project is to show that the advantages of using dynamic query forms for database over the existing static forms for database. We reach to user satisfaction using ranking attribut

Optimization Technique for Efficient Dynamic Query Forms with Keyword Search and NoSQL

Modern web database as well as scientific database maintains tremendous and heterogeneous that is unstructured data. In order to mine this data traditional data mining technologies cannot work properly. These real word databases may contain hundreds or even thousands of relations and attributes. Latest trends like Big data and cloud computing that leads to the adoption of NoSQL which simply means Not Only SQL. In current scenario Most of the web applications are hosted in cloud and that available through internet. This create explosion in number of concurrent users. So the technique to handle unstructured data is proposed in our work named as Dynamic query forms with nosql. This system presents dynamic query form interface for database exploration of an organization. In this system document oriented NoSQL database is used for that purpose MONGODB is used which support dynamic queries that do not require predefined map reduce function. And further the process generation of a query form is an iterative process guided by user. At each step system automatically generate ranking list of form components and user adds the desired form component into query form and submit queries to view query result. Two traditional measures to evaluate the quality of query result i.e, precision and recall is presented. Quality measures can be derived using overall performance measure as Fscore DOI: 10.17762/ijritcc2321-8169.15070

Contextual Media Retrieval Using Natural Language Queries

The widespread integration of cameras in hand-held and head-worn devices as well as the ability to share content online enables a large and diverse visual capture of the world that millions of users build up collectively every day. We envision these images as well as associated meta information, such as GPS coordinates and timestamps, to form a collective visual memory that can be queried while automatically taking the ever-changing context of mobile users into account. As a first step towards this vision, in this work we present Xplore-M-Ego: a novel media retrieval system that allows users to query a dynamic database of images and videos using spatio-temporal natural language queries. We evaluate our system using a new dataset of real user queries as well as through a usability study. One key finding is that there is a considerable amount of inter-user variability, for example in the resolution of spatial relations in natural language utterances. We show that our retrieval system can cope with this variability using personalisation through an online learning-based retrieval formulation.Comment: 8 pages, 9 figures, 1 tabl

First-Class Functions for First-Order Database Engines

We describe Query Defunctionalization which enables off-the-shelf first-order database engines to process queries over first-class functions. Support for first-class functions is characterized by the ability to treat functions like regular data items that can be constructed at query runtime, passed to or returned from other (higher-order) functions, assigned to variables, and stored in persistent data structures. Query defunctionalization is a non-invasive approach that transforms such function-centric queries into the data-centric operations implemented by common query processors. Experiments with XQuery and PL/SQL database systems demonstrate that first-order database engines can faithfully and efficiently support the expressive "functions as data" paradigm.Comment: Proceedings of the 14th International Symposium on Database Programming Languages (DBPL 2013), August 30, 2013, Riva del Garda, Trento, Ital